The subject matter described herein relates generally to the field of imaging and image processing and more particularly, to systems and methods for acquiring images of high dynamic range scenes or imaging a scene under low light conditions.
Electronic devices such as mobile phones, personal digital assistants, portable computers and the like may comprise a camera to capture digital images. By way of example, a mobile phone may comprise one or more cameras to capture digital images. Electronic devices may be equipped with an image signal processing pipeline to capture images collected by the camera, process the images and store the images in memory and/or display the images.
In some instances the dynamic range of natural scenes may exceed the dynamic range of the camera acquisition system, resulting in loss of detail in the final image in certain regions of an image. Similarly, under low light conditions, camera images may suffer from significant noise that affects the fidelity of scene capture.
Techniques to accommodate dynamic range issues in digital photography include processing image stacks to extend dynamic range or reduce noise, far less attention has been paid to determining optimal ways of acquiring these image stacks. However, much of the work in the literature assumes that the characteristics of the scene is already known, and captures a predetermined number of images that may be more than sufficient. Since the multi-image approach is susceptible to motion between captured images, unnecessarily capturing more frames may result in poorer merging artifacts and require more expensive reconstruction algorithms to handle motion and misalignments between different images. Thus, techniques to select a number of images in an image stack, may find utility in digital photography, especially in resource-constrained systems such as hand-held mobile devices.